Epigenomic Tool Breakthrough Has Implications for Identifying Disease Processes

Article ID: 690633

Released: 6-Mar-2018 12:05 PM EST

Source Newsroom: Virginia Tech

Newswise — A major advancement has been made on how epigenomics are studied that permits mapping a genome-scale profile of epigenetic changes using less than a couple hundred of cells, a factor of 100-300 reduction in the sample amount compared to existing alternatives. Led by Virginia Tech’s Chang Lu, the innovative method has implications for deciphering disease processes such as schizophrenia, cancer and inflammation that involve epigenetic mechanisms.

The research, published in the journal Nature Biomedical Engineering, entitled “Cell-type-specific brain methylomes profiled via ultralow-input microfluidics” (doi:10.1038/s41551-018-0204-3) is a collaboration with Lu, the Fred W. Bull professor of chemical engineering; Sai Ma, a biomedical engineering and mechanics graduate student and first author of the paper; Hehuang Xie, an associate professor at biomedical sciences and pathobiology in the Virginia-Maryland College of Veterinary Medicine and of the Biocomplexity Institute of Virginia Tech; and Javier González-Maeso, an associate professor in the School of Medicine at Virginia Commonwealth University.

“If you think of the DNA sequence, or genetics, as a blue print for building a house, then epigenetics dictates how this blue print is followed at a given time and environment. Different architects may carry out the same blueprint quite differently,” Lu explained. “That is why identical twins sharing the same DNA sequence may have very different diseases.”   

DNA treatment followed by whole-genome sequencing allows for characterizing the genome-wide epigenetic changes, or epigenomes. However, current assays require more than twenty thousand cells per test. In contrast, Lu’s new method, microfluidic diffusion-based reduced representative bisulfate sequencing known as MID-RRBS, can collect the same information with as few as 60 cells.

In order to conduct the chemical treatment of DNA, Lu’s team designed a microfluidic chip with micrometer channels and chambers and implemented a diffusion-based process for changing reagents needed for the multi-step process. The device and protocol dramatically decreased DNA loss during the process.

Using the new technique to examine different cell types from a mouse brain, the team focused on one type of epigenomic change called DNA methylation. Their results show that the technology had no problem to differentiate neurons (the cells that transmit signals in brain) from glia that provide support to neurons, by profiling and comparing genome-scale DNA methylation patterns of the two cell types.

With González-Maeso’s lab, the Virginia Tech team observed that a number of genes in neurons of mouse brain experienced changes in DNA methylation after chronic administration of an antipsychotic drug, clozapine. It has long been speculated that epigenetic changes constitute an important part of the overall molecular machinery involved in mental disease development. The results show that an antipsychotic drug potentially controls a mental disease by creating changes in the same system.

 “Screening human cells for their epigenetic changes is important in devising procedures and drugs that combat diseases,” Lu explained. “In addition to brain research, our technology will be tremendously useful for looking into a large number of disease processes such as cancer and inflammation that also involve epigenetic mechanisms.”

Less is more. By allowing for epigenome profiling with a small amount of tissues, Lu’s method aids in pinpointing moleclar-level changes due to drugs and diseases. It’s an important step at the nexus of many fields, bridging patient needs, medical solutions, and biological understanding.

The work was funded by grants from National Human Genome Research Institute, National Institute of Biomedical Imaging and Bioengineering, National Institute of Mental Health, and National Institute of Neurological Disorders and Stroke.

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